import mmpose
print(mmpose.__version__)
from mmpose.apis import MMPoseInferencer
inferencer = MMPoseInferencer('human')
print("[INFO]: Imported modules!!")

import gradio as gr

def greet(photo):
    print("[INFO]: Downloaded models!")
    result_generator = inferencer(photo)

    print("[INFO]: Visualizing results!")
    vis, pred = next(result_generator)
    return vis

# # specify detection model by alias
# # the available aliases include 'human', 'hand', 'face', 'animal',
# # as well as any additional aliases defined in mmdet
# inferencer = MMPoseInferencer(
#     # suppose the pose estimator is trained on custom dataset
#     pose2d='custom_human_pose_estimator.py',
#     pose2d_weights='custom_human_pose_estimator.pth',
#     det_model='human'
# )
if __name__ == '__main__':

    demo = gr.Interface(fn=greet, inputs=gr.Image(source="webcam"), outputs=gr.Image())
    
    demo.launch()